Optimization of neural network model using modified bat-inspired algorithm

- A modified bat algorithm with a new solution representation for both optimizing the weights and structure of ANNs is proposed.
- To improve the exploration and exploitation capability of bat algorithm some modifications based on chaotic map on bat algorithm are studied.
- The Taguchi method is used to tune the parameters of the algorithm.
- Six classifications and two time series benchmark datasets are used to test the performance of the proposed approach in terms of classification and prediction accuracy.
- Finally, our best method is applied to a real-world problem, namely to predict the future values of rainfall data in Selangor at Malaysia.